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This paper presents a comprehensive study of forecasting a day-ahead of load and locational marginal pricing (LMP) using artificial intelligent systems. An artificial neural network (ANN) is trained with a stochastic optimization technique called particle swarm optimization (PSO). This training algorithm works to adjust the network weights and biases as to minimize the error function. Wavelet transformed...
The short-term load is nonlinear, and the change of it is influenced by various factors. Be one of them, the temperature is considered the main influencing factor. Not only the temperature of the day to be forecasted take a great influence on the load, but also the temperature of the previous days does. Especially in summer, the influence of the continuous high temperature on the load is different...
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